from sklearn_benchmarks.reporting.hp_match import HPMatchReporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = HPMatchReporting(against_lib="sklearnex", config="config.yml")
reporting.make_report()
We assume here there is a perfect match between the hyperparameters of both librairies. For a given set of parameters and a given dataset, we compute the speedup
time scikit-learn / time sklearnex. For instance, a speedup of 2 means that sklearnex is twice as fast as scikit-learn for a given set of parameters and a given dataset.
KNeighborsClassifier_brute_force¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
| estimator | function | n_samples_train | n_samples | n_features | accuracy_score_sklearn | accuracy_score_sklearnex | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 0.663 | 0.687 | 0.024 |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 0.757 | 0.742 | 0.015 |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 0.882 | 0.875 | 0.007 |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 1.000 | 0.000 | 1.000 |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 0.882 | 0.875 | 0.007 |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 1.000 | 0.000 | 1.000 |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 0.757 | 0.742 | 0.015 |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 0.663 | 0.687 | 0.024 |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 0.896 | 0.967 | 0.071 |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 0.922 | 0.974 | 0.052 |
| 25 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 0.929 | 0.975 | 0.046 |
| 28 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 0.929 | 0.975 | 0.046 |
| 31 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 0.922 | 0.974 | 0.052 |
| 34 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 0.896 | 0.967 | 0.071 |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.001 | NaN | 5.957 | 0.0 | -1 | 1 | NaN | 0.053 | 0.004 | NaN | 0.256 | 0.257 | See | See |
| 3 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.001 | NaN | 6.199 | 0.0 | -1 | 5 | NaN | 0.051 | 0.001 | NaN | 0.254 | 0.254 | See | See |
| 6 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.014 | 0.001 | NaN | 5.674 | 0.0 | 1 | 100 | NaN | 0.051 | 0.001 | NaN | 0.278 | 0.278 | See | See |
| 9 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.000 | NaN | 6.445 | 0.0 | -1 | 100 | NaN | 0.051 | 0.001 | NaN | 0.245 | 0.245 | See | See |
| 12 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.001 | NaN | 6.560 | 0.0 | 1 | 5 | NaN | 0.053 | 0.002 | NaN | 0.231 | 0.231 | See | See |
| 15 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.001 | NaN | 6.386 | 0.0 | 1 | 1 | NaN | 0.050 | 0.001 | NaN | 0.250 | 0.250 | See | See |
| 18 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | NaN | 0.431 | 0.0 | -1 | 1 | NaN | 0.007 | 0.000 | NaN | 0.535 | 0.535 | See | See |
| 21 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.001 | NaN | 0.362 | 0.0 | -1 | 5 | NaN | 0.007 | 0.000 | NaN | 0.611 | 0.611 | See | See |
| 24 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.001 | NaN | 0.405 | 0.0 | 1 | 100 | NaN | 0.007 | 0.000 | NaN | 0.561 | 0.562 | See | See |
| 27 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | NaN | 0.406 | 0.0 | -1 | 100 | NaN | 0.007 | 0.000 | NaN | 0.548 | 0.548 | See | See |
| 30 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | NaN | 0.400 | 0.0 | 1 | 5 | NaN | 0.007 | 0.000 | NaN | 0.559 | 0.560 | See | See |
| 33 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | NaN | 0.420 | 0.0 | 1 | 1 | NaN | 0.008 | 0.001 | NaN | 0.507 | 0.509 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.124 | 0.217 | NaN | 0.000 | 0.002 | -1 | 1 | 0.663 | 0.404 | 0.009 | 0.687 | 5.261 | 5.262 | See | See |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.025 | 0.003 | NaN | 0.000 | 0.025 | -1 | 1 | 1.000 | 0.011 | 0.001 | 1.000 | 2.326 | 2.332 | See | See |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.700 | 0.059 | NaN | 0.000 | 0.003 | -1 | 5 | 0.757 | 0.402 | 0.008 | 0.742 | 6.717 | 6.719 | See | See |
| 5 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.028 | 0.003 | NaN | 0.000 | 0.028 | -1 | 5 | 1.000 | 0.011 | 0.001 | 1.000 | 2.592 | 2.601 | See | See |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.111 | 0.038 | NaN | 0.000 | 0.002 | 1 | 100 | 0.882 | 0.449 | 0.007 | 0.875 | 4.702 | 4.702 | See | See |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.001 | NaN | 0.000 | 0.023 | 1 | 100 | 1.000 | 0.011 | 0.001 | 0.000 | 2.148 | 2.150 | See | See |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.666 | 0.107 | NaN | 0.000 | 0.003 | -1 | 100 | 0.882 | 0.453 | 0.007 | 0.875 | 5.887 | 5.888 | See | See |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.025 | 0.003 | NaN | 0.000 | 0.025 | -1 | 100 | 1.000 | 0.011 | 0.000 | 0.000 | 2.260 | 2.262 | See | See |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.067 | 0.015 | NaN | 0.000 | 0.002 | 1 | 5 | 0.757 | 0.403 | 0.008 | 0.742 | 5.124 | 5.125 | See | See |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.000 | NaN | 0.000 | 0.023 | 1 | 5 | 1.000 | 0.011 | 0.000 | 1.000 | 2.172 | 2.173 | See | See |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.385 | 0.012 | NaN | 0.001 | 0.001 | 1 | 1 | 0.663 | 0.400 | 0.010 | 0.687 | 3.462 | 3.463 | See | See |
| 17 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.022 | 0.001 | NaN | 0.000 | 0.022 | 1 | 1 | 1.000 | 0.010 | 0.000 | 1.000 | 2.138 | 2.140 | See | See |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.602 | 0.031 | NaN | 0.000 | 0.002 | -1 | 1 | 0.896 | 0.088 | 0.003 | 0.967 | 18.259 | 18.272 | See | See |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.005 | 0.002 | NaN | 0.000 | 0.005 | -1 | 1 | 1.000 | 0.001 | 0.000 | 1.000 | 8.283 | 8.342 | See | See |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.305 | 0.029 | NaN | 0.000 | 0.002 | -1 | 5 | 0.922 | 0.090 | 0.001 | 0.974 | 25.753 | 25.755 | See | See |
| 23 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.007 | 0.005 | NaN | 0.000 | 0.007 | -1 | 5 | 1.000 | 0.001 | 0.000 | 1.000 | 11.955 | 12.092 | See | See |
| 25 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.832 | 0.016 | NaN | 0.000 | 0.002 | 1 | 100 | 0.929 | 0.140 | 0.003 | 0.975 | 13.127 | 13.129 | See | See |
| 26 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | NaN | 0.000 | 0.003 | 1 | 100 | 1.000 | 0.001 | 0.000 | 1.000 | 4.287 | 4.300 | See | See |
| 28 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.329 | 0.040 | NaN | 0.000 | 0.002 | -1 | 100 | 0.929 | 0.140 | 0.005 | 0.975 | 16.617 | 16.630 | See | See |
| 29 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.007 | 0.004 | NaN | 0.000 | 0.007 | -1 | 100 | 1.000 | 0.001 | 0.000 | 1.000 | 10.580 | 10.636 | See | See |
| 31 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.843 | 0.022 | NaN | 0.000 | 0.002 | 1 | 5 | 0.922 | 0.089 | 0.001 | 0.974 | 20.767 | 20.769 | See | See |
| 32 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | NaN | 0.000 | 0.003 | 1 | 5 | 1.000 | 0.001 | 0.000 | 1.000 | 5.141 | 5.177 | See | See |
| 34 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.165 | 0.014 | NaN | 0.000 | 0.001 | 1 | 1 | 0.896 | 0.089 | 0.003 | 0.967 | 13.114 | 13.123 | See | See |
| 35 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.002 | 0.000 | NaN | 0.000 | 0.002 | 1 | 1 | 1.000 | 0.001 | 0.000 | 1.000 | 3.586 | 3.606 | See | See |
KNeighborsClassifier_kd_tree¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
| estimator | function | n_samples_train | n_samples | n_features | accuracy_score_sklearn | accuracy_score_sklearnex | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.929 | 0.910 | 0.019 |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.946 | 0.941 | 0.005 |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.951 | 0.940 | 0.011 |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.951 | 0.940 | 0.011 |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.946 | 0.941 | 0.005 |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.929 | 0.910 | 0.019 |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.891 | 0.879 | 0.012 |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.911 | 0.905 | 0.006 |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.894 | 0.917 | 0.023 |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.894 | 0.917 | 0.023 |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.911 | 0.905 | 0.006 |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.891 | 0.879 | 0.012 |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2.291 | 0.038 | NaN | 0.035 | 0.0 | -1 | 1 | NaN | 0.753 | 0.098 | NaN | 3.040 | 3.066 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.027 | 0.042 | NaN | 0.026 | 0.0 | -1 | 5 | NaN | 0.694 | 0.007 | NaN | 4.364 | 4.365 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.222 | 0.189 | NaN | 0.025 | 0.0 | 1 | 100 | NaN | 0.697 | 0.028 | NaN | 4.623 | 4.626 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.173 | 0.090 | NaN | 0.025 | 0.0 | -1 | 100 | NaN | 0.702 | 0.022 | NaN | 4.519 | 4.521 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.116 | 0.071 | NaN | 0.026 | 0.0 | 1 | 5 | NaN | 0.687 | 0.009 | NaN | 4.536 | 4.536 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.137 | 0.056 | NaN | 0.026 | 0.0 | 1 | 1 | NaN | 0.695 | 0.014 | NaN | 4.512 | 4.513 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.001 | NaN | 0.015 | 0.0 | -1 | 1 | NaN | 0.004 | 0.002 | NaN | 0.277 | 0.320 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.024 | 0.0 | -1 | 5 | NaN | 0.002 | 0.001 | NaN | 0.427 | 0.585 | See | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.027 | 0.0 | 1 | 100 | NaN | 0.001 | 0.000 | NaN | 0.474 | 0.507 | See | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.027 | 0.0 | -1 | 100 | NaN | 0.001 | 0.000 | NaN | 0.613 | 0.616 | See | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.026 | 0.0 | 1 | 5 | NaN | 0.001 | 0.000 | NaN | 0.587 | 0.591 | See | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.026 | 0.0 | 1 | 1 | NaN | 0.001 | 0.000 | NaN | 0.685 | 0.688 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.841 | 1.153 | NaN | 0.000 | 0.001 | -1 | 1 | 0.929 | 0.111 | 0.005 | 0.910 | 7.558 | 7.565 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.000 | NaN | 0.000 | 0.003 | -1 | 1 | 1.000 | 0.000 | 0.000 | 1.000 | 9.506 | 10.981 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.944 | 0.346 | NaN | 0.000 | 0.001 | -1 | 5 | 0.946 | 0.198 | 0.006 | 0.941 | 4.769 | 4.771 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.000 | NaN | 0.000 | 0.003 | -1 | 5 | 1.000 | 0.000 | 0.000 | 1.000 | 6.248 | 6.490 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 4.863 | 0.483 | NaN | 0.000 | 0.005 | 1 | 100 | 0.951 | 0.608 | 0.008 | 0.940 | 8.002 | 8.003 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | NaN | 0.000 | 0.003 | 1 | 100 | 1.000 | 0.001 | 0.000 | 1.000 | 3.323 | 3.416 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2.913 | 0.312 | NaN | 0.000 | 0.003 | -1 | 100 | 0.951 | 0.589 | 0.009 | 0.940 | 4.946 | 4.946 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.004 | 0.001 | NaN | 0.000 | 0.004 | -1 | 100 | 1.000 | 0.001 | 0.000 | 1.000 | 5.097 | 5.220 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.538 | 0.458 | NaN | 0.000 | 0.002 | 1 | 5 | 0.946 | 0.199 | 0.005 | 0.941 | 7.724 | 7.726 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.001 | NaN | 0.000 | 0.001 | 1 | 5 | 1.000 | 0.000 | 0.000 | 1.000 | 3.357 | 3.562 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.855 | 0.388 | NaN | 0.000 | 0.001 | 1 | 1 | 0.929 | 0.110 | 0.004 | 0.910 | 7.756 | 7.760 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 1 | 1.000 | 0.000 | 0.000 | 1.000 | 3.071 | 3.116 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.029 | 0.016 | NaN | 0.001 | 0.000 | -1 | 1 | 0.891 | 0.001 | 0.000 | 0.879 | 45.629 | 46.159 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.003 | 0.001 | NaN | 0.000 | 0.003 | -1 | 1 | 1.000 | 0.000 | 0.000 | 1.000 | 22.646 | 22.853 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.025 | 0.001 | NaN | 0.001 | 0.000 | -1 | 5 | 0.911 | 0.001 | 0.000 | 0.905 | 27.278 | 27.306 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | NaN | 0.000 | 0.002 | -1 | 5 | 1.000 | 0.000 | 0.000 | 1.000 | 17.007 | 17.115 | See | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.038 | 0.012 | NaN | 0.000 | 0.000 | 1 | 100 | 0.894 | 0.005 | 0.000 | 0.917 | 7.201 | 7.210 | See | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 100 | 1.000 | 0.000 | 0.000 | 1.000 | 7.367 | 7.432 | See | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.042 | 0.007 | NaN | 0.000 | 0.000 | -1 | 100 | 0.894 | 0.006 | 0.001 | 0.917 | 7.094 | 7.293 | See | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | NaN | 0.000 | 0.002 | -1 | 100 | 1.000 | 0.000 | 0.000 | 1.000 | 13.244 | 13.493 | See | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.022 | 0.001 | NaN | 0.001 | 0.000 | 1 | 5 | 0.911 | 0.001 | 0.000 | 0.905 | 24.360 | 24.427 | See | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 5 | 1.000 | 0.000 | 0.000 | 1.000 | 6.048 | 6.093 | See | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.021 | 0.001 | NaN | 0.001 | 0.000 | 1 | 1 | 0.891 | 0.001 | 0.000 | 0.879 | 37.171 | 37.246 | See | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 1 | 1.000 | 0.000 | 0.000 | 1.000 | 4.994 | 5.130 | See | See |
KMeans_tall¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=3, max_iter=30, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | adjusted_rand_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.593 | 0.267 | 30 | 0.027 | 0.0 | random | NaN | 0.275 | 0.012 | NaN | 2.157 | 2.159 | See | See |
| 3 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.586 | 0.020 | 30 | 0.027 | 0.0 | k-means++ | NaN | 0.308 | 0.005 | NaN | 1.903 | 1.904 | See | See |
| 6 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 7.029 | 0.264 | 30 | 0.114 | 0.0 | random | NaN | 4.000 | 0.138 | NaN | 1.757 | 1.758 | See | See |
| 9 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 7.337 | 0.096 | 30 | 0.109 | 0.0 | k-means++ | NaN | 4.185 | 0.071 | NaN | 1.753 | 1.753 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | adjusted_rand_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.000 | 30 | 0.009 | 0.000 | random | 0.001 | 0.0 | 0.0 | 0.001 | 7.288 | 9.385 | See | See |
| 2 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.002 | 0.000 | 30 | 0.000 | 0.002 | random | 1.000 | 0.0 | 0.0 | 1.000 | 11.397 | 11.462 | See | See |
| 4 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.000 | 30 | 0.009 | 0.000 | k-means++ | 0.001 | 0.0 | 0.0 | 0.001 | 9.383 | 9.628 | See | See |
| 5 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.002 | 0.000 | 30 | 0.000 | 0.002 | k-means++ | 1.000 | 0.0 | 0.0 | 1.000 | 11.076 | 11.115 | See | See |
| 7 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.000 | 30 | 0.414 | 0.000 | random | 0.002 | 0.0 | 0.0 | 0.002 | 7.020 | 7.256 | See | See |
| 8 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.002 | 0.000 | 30 | 0.001 | 0.002 | random | 1.000 | 0.0 | 0.0 | 1.000 | 9.801 | 9.866 | See | See |
| 10 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.001 | 30 | 0.393 | 0.000 | k-means++ | 0.002 | 0.0 | 0.0 | 0.001 | 7.217 | 7.402 | See | See |
| 11 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.002 | 0.000 | 30 | 0.000 | 0.002 | k-means++ | 1.000 | 0.0 | 0.0 | 1.000 | 12.583 | 12.643 | See | See |
KMeans_short¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=300, max_iter=20, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | adjusted_rand_score_sklearn | adjusted_rand_score_sklearnex | diff_adjusted_rand_scores | |
|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 0.000126 | -0.000965 | 0.001090 |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 0.001245 | -0.000750 | 0.001995 |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 0.278733 | 0.293767 | 0.015034 |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 0.317011 | 0.256968 | 0.060044 |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | adjusted_rand_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 10000 | 10000 | 2 | 0.100 | 0.003 | 20 | 0.002 | 0.0 | random | NaN | 0.050 | 0.002 | NaN | 2.003 | 2.005 | See | See |
| 3 | KMeans_short | fit | 10000 | 10000 | 2 | 0.297 | 0.013 | 20 | 0.001 | 0.0 | k-means++ | NaN | 0.131 | 0.003 | NaN | 2.267 | 2.267 | See | See |
| 6 | KMeans_short | fit | 10000 | 10000 | 100 | 0.319 | 0.009 | 20 | 0.025 | 0.0 | random | NaN | 0.254 | 0.006 | NaN | 1.258 | 1.258 | See | See |
| 9 | KMeans_short | fit | 10000 | 10000 | 100 | 1.088 | 0.011 | 20 | 0.007 | 0.0 | k-means++ | NaN | 0.609 | 0.010 | NaN | 1.788 | 1.789 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | adjusted_rand_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.0 | 20 | 0.008 | 0.000 | random | 0.000 | 0.001 | 0.0 | -0.001 | 3.472 | 3.485 | See | See |
| 2 | KMeans_short | predict | 10000 | 1 | 2 | 0.002 | 0.0 | 20 | 0.000 | 0.002 | random | 1.000 | 0.000 | 0.0 | 1.000 | 11.291 | 11.342 | See | See |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.0 | 20 | 0.008 | 0.000 | k-means++ | 0.001 | 0.001 | 0.0 | -0.001 | 3.251 | 3.271 | See | See |
| 5 | KMeans_short | predict | 10000 | 1 | 2 | 0.002 | 0.0 | 20 | 0.000 | 0.002 | k-means++ | 1.000 | 0.000 | 0.0 | 1.000 | 9.916 | 9.942 | See | See |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 0.003 | 0.0 | 20 | 0.255 | 0.000 | random | 0.279 | 0.001 | 0.0 | 0.294 | 2.165 | 2.177 | See | See |
| 8 | KMeans_short | predict | 10000 | 1 | 100 | 0.002 | 0.0 | 20 | 0.000 | 0.002 | random | 1.000 | 0.000 | 0.0 | 1.000 | 9.158 | 9.221 | See | See |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 0.003 | 0.0 | 20 | 0.255 | 0.000 | k-means++ | 0.317 | 0.001 | 0.0 | 0.257 | 2.151 | 2.157 | See | See |
| 11 | KMeans_short | predict | 10000 | 1 | 100 | 0.002 | 0.0 | 20 | 0.000 | 0.002 | k-means++ | 1.000 | 0.000 | 0.0 | 1.000 | 9.895 | 9.924 | See | See |
LogisticRegression¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: penalty=l2, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=nan, random_state=nan, solver=lbfgs, max_iter=100, multi_class=auto, verbose=0, warm_start=False, n_jobs=nan, l1_ratio=nan.
| estimator | function | n_samples_train | n_samples | n_features | accuracy_score_sklearn | accuracy_score_sklearnex | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | 0.56 | 0.55 | 0.01 |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | 0.35 | 0.28 | 0.07 |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 1000000 | 1000000 | 100 | 15.559 | 0.489 | [20] | 0.051 | 0.000 | NaN | NaN | NaN | NaN | NaN | 2.956 | 0.044 | NaN | 5.265 | 5.265 | See | See |
| 3 | LogisticRegression | fit | 1000 | 1000 | 10000 | 1.446 | 0.683 | [26] | 0.055 | 0.001 | NaN | NaN | NaN | NaN | NaN | 1.139 | 0.032 | NaN | 1.269 | 1.270 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | 0.000 | 0.001 | [20] | 1.618 | 0.0 | NaN | NaN | NaN | NaN | 0.56 | 0.001 | 0.001 | 0.55 | 0.570 | 1.064 | See | See |
| 2 | LogisticRegression | predict | 1000000 | 1 | 100 | 0.000 | 0.000 | [20] | 0.011 | 0.0 | NaN | NaN | NaN | NaN | 1.00 | 0.000 | 0.000 | 1.00 | 0.334 | 0.336 | See | See |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | 0.002 | 0.000 | [26] | 3.358 | 0.0 | NaN | NaN | NaN | NaN | 0.35 | 0.006 | 0.001 | 0.28 | 0.377 | 0.379 | See | See |
| 5 | LogisticRegression | predict | 1000 | 1 | 10000 | 0.000 | 0.000 | [26] | 0.703 | 0.0 | NaN | NaN | NaN | NaN | 0.00 | 0.002 | 0.000 | 0.00 | 0.066 | 0.066 | See | See |
Ridge¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: alpha=1.0, fit_intercept=True, normalize=deprecated, copy_X=True, max_iter=nan, tol=0.001, solver=auto, random_state=nan.
| estimator | function | n_samples_train | n_samples | n_features | r2_score_sklearn | r2_score_sklearnex | diff_r2_scores | |
|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | 0.082567 | 0.122191 | 0.039624 |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | max_iter | random_state | r2_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | r2_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1000 | 1000 | 10000 | 0.293 | 0.006 | NaN | 0.273 | 0.0 | NaN | NaN | NaN | 0.308 | 0.011 | NaN | 0.951 | 0.952 | See | See |
| 3 | Ridge | fit | 1000000 | 1000000 | 100 | 1.328 | 0.075 | NaN | 0.602 | 0.0 | NaN | NaN | NaN | 0.475 | 0.279 | NaN | 2.793 | 3.238 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | max_iter | random_state | r2_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | r2_score_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | 0.012 | 0.0 | NaN | 6.481 | 0.0 | NaN | NaN | 0.083 | 0.020 | 0.001 | 0.122 | 0.617 | 0.618 | See | See |
| 2 | Ridge | predict | 1000 | 1 | 10000 | 0.000 | 0.0 | NaN | 0.733 | 0.0 | NaN | NaN | NaN | 0.000 | 0.000 | NaN | 0.812 | 0.830 | See | See |
| 4 | Ridge | predict | 1000000 | 1000 | 100 | 0.000 | 0.0 | NaN | 5.320 | 0.0 | NaN | NaN | 1.000 | 0.001 | 0.001 | 1.000 | 0.294 | 0.563 | See | See |
| 5 | Ridge | predict | 1000000 | 1 | 100 | 0.000 | 0.0 | NaN | 0.013 | 0.0 | NaN | NaN | NaN | 0.000 | 0.000 | NaN | 0.597 | 0.609 | See | See |